時間に迷う?未知の測定遅延を伴う支援慣性航法における連続対称性と識別可能性
Lost in Time? Continuous Symmetry and Identifiability in Aided Inertial Navigation with Unknown Measurement Delays
慣性航法システムにおいて、センサ測定の未知の時間遅延が状態推定に与える影響を分析し、軌道の形状によって遅延と航法状態の一意な推定が可能かどうかが決まることを、ガリレイ群を用いて特徴付けた論文。
詳しい要約
1. どんなもの?
2. 先行研究と比べてどこがすごい?
3. 技術・手法の肝は?
4. どうやって有効だと検証した?
5. 議論はある?
6. 次に読むべき論文は?
※ AIが要旨から生成した要約です。正確性は原文をご確認ください。
著者: Jonathan Kelly, Phone Thiha Kyaw, Mattew Giamou
分類: cs.RO, cs.SY, eess.SY
原文アブストラクト
In many multisensor systems, measurements from different sensors are subject to unknown relative time delays. Accurate state estimation requires that delays be accounted for and, when possible, calibrated online. We consider the case of aided inertial navigation, where measurements from a single aiding sensor are subject to an unknown but constant delay relative to the inertial measurement stream, and study the identifiability of the resulting system. Critically, identifiability depends not only on the temporal structure of the measurements, but also on the shape of the vehicle trajectory: some trajectories are sufficiently informative to support unique recovery of the delay and the navigation state, while others are not. Using the special Galilean Lie group, we characterize a broad family of uninformative trajectories, each generated by a constant element of the Galilean Lie algebra. We show that, along any such trajectory, the delayed measurement model admits a continuous symmetry that prevents unique recovery of the delay and the navigation state. We connect this symmetry-based characterization to the familiar linearized, Jacobian-based analysis. Although our development is motivated by aided navigation, the underlying ideas apply more generally to estimation problems on Lie groups with delayed measurements.
